Early object detection for unprotected turns

ABSTRACT

A system and method is provided for early detection of objects by a perception system of a vehicle, and triggering a precautionary action by the vehicle in response without waiting for a more precise detection. The vehicle has a multi-level sensor range, wherein a first level of the sensor range is adjacent an outer bounds of the sensor range and has a first confidence value, and a second level of the sensor range is within the first range and has a second higher confidence value. In situations when oncoming traffic is traveling at a high rate of speed, the vehicle responds to noisier detections, or objects perceived with a lower degree of confidence, rather than waiting for verification which may come too late.

BACKGROUND

Autonomous vehicles, for instance, vehicles that do not require a humandriver, can be used to aid in the transport of passengers or items fromone location to another. Such vehicles may operate in a fully autonomousmode where passengers may provide some initial input, such as a pickupor destination location, and the vehicle maneuvers itself to thatlocation.

While some autonomous vehicles are operable in a semi-autonomous mode,such as where a human driver takes over control of the vehicle in somecircumstances, it is nevertheless important for the autonomous vehicleto operate in the safest manner possible.

BRIEF SUMMARY

One aspect of the disclosure provides a method for maneuvering avehicle. The method includes defining, for an autonomous vehicle havingone or more sensors, a first sensor range having a first associatedconfidence value, the first sensor range adjacent an outer bound ofreach of the one or more sensors, and defining a second sensor range,the second sensor range having a second associated confidence value thatis higher than the first confidence value, the second sensor range beingwithin the first sensor range and closer to the one or more sensors thanthe first sensor range. The method further includes receiving, at one ormore processors, input from the one or more sensors, detecting, by theone or more processors based on the input received from the one or moresensors, an object within the first sensor range of the vehicle, andcausing the vehicle to take a first action in response to detecting theobject within the first sensor range, prior to the object being detectedwithin the second sensor range, wherein the first action comprises atleast one of yielding, ceasing acceleration, decelerating, or switchinglanes. In some examples, the method may further include detecting, bythe one or more processors based on further input received from the oneor more sensors, that the object has moved into the second sensor rangeof the vehicle, and validating the detection of the object within thefirst sensor range based on the detection of the object within thesecond sensor range.

The vehicle, when receiving the input from the one or more sensors, maybe waiting to merge onto a roadway having a speed limit of 45 miles perhour or higher. In this example, the object detected within the firstsensor range may be a second vehicle traveling on the roadway, and thefirst action may include continuing to wait to merge onto the roadway.In another example, the vehicle, when receiving the input from the oneor more sensors, is traveling in a first lane of a roadway having aspeed limit of 45 miles per hour or higher, the object detected withinthe first sensor range is a second vehicle traveling in the first or asecond lane on the roadway, and approaching the vehicle from behind, andthe first action includes changing lanes away from the lane in which thesecond vehicle is traveling. In yet a further example, the vehicle, whenreceiving the input from the one or more sensors, is making anunprotected turn onto a roadway, the object detected within the firstsensor range is a second vehicle traveling along the roadway towards thevehicle, and the first action may include waiting to make theunprotected turn until the first and second sensor ranges are clear.

Another aspect of the disclosure provides a system, including one ormore sensors, the one or more sensors having a first defined rangeadjacent an outer bound of reach of the one or more sensors, the firstdefined range having a first associated confidence value, and a seconddefined range within the first sensor range and closer to the one ormore sensors than the first sensor range, the second defined rangehaving a second associated confidence value that is higher than thefirst confidence value. The system further includes one or moreprocessors in communication with the one or more sensors, wherein theone or more processors are configured to receive input from the one ormore sensors, detect, based on the input received from the one or moresensors, an object within the first sensor range of the vehicle, andcause the vehicle to take a first action in response to detecting theobject within the first sensor range, prior to the object being detectedwithin the second sensor range, wherein the first action comprises atleast one of yielding, ceasing acceleration, decelerating, or switchinglanes.

Yet another aspect of the disclosure provides a vehicle, including adriving system including at least an acceleration system, a brakingsystem, and a steering system, and a perception system including atleast one or more sensors. The one or more sensors have a first definedrange adjacent an outer bound of reach of the one or more sensors, thefirst defined range having a first associated confidence value, and asecond defined range within the first sensor range and closer to the oneor more sensors than the first sensor range, the second defined rangehaving a second associated confidence value that is higher than thefirst confidence value. The vehicle further includes a control systemincluding at least one or more processors in communication with the oneor more sensors. The one or more processors are configured to receiveinput from the one or more sensors, detect, based on the input receivedfrom the one or more sensors, an object within the first sensor range ofthe vehicle, and cause the vehicle to take a first action in response todetecting the object within the first sensor range, prior to the objectbeing detected within the second sensor range, wherein the first actioncomprises at least one of yielding, ceasing acceleration, decelerating,or switching lanes. The vehicle of may in some examples be autonomous.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a functional diagram of an example vehicle in accordance withan exemplary embodiment.

FIG. 2 is an example external view of a vehicle in accordance withaspects of the disclosure.

FIG. 3 is an example bird's eye view of a first sensor range and asecond sensor range of the vehicle in accordance with an exemplaryembodiment.

FIG. 4 is an example flow diagram in accordance with aspects of thedisclosure.

FIG. 5 is an example bird's eye view of the vehicle reacting within ageographic area of a first type in accordance with aspects of thedisclosure.

FIG. 6 is another example bird's eye view of the vehicle reacting withinthe geographic area of FIG. 5 in accordance with aspects of thedisclosure.

FIG. 7 is another example bird's eye view of the vehicle reacting withinthe geographic area of FIG. 5 in accordance with aspects of thedisclosure.

FIG. 8 is an example bird's eye view of the vehicle reacting within ageographic area of a second type in accordance with aspects of thedisclosure.

DETAILED DESCRIPTION

Overview

The technology relates to detection of objects by an autonomous vehicle.In particular, in some driving situations, the autonomous vehicle mayoperate based on an early detection of an object, without waiting for amore precise detection. For example, whereas an autonomous vehicle maytypically wait until objects are detected within a sensor range having arelatively high associated confidence value, the present technologyprovides for earlier detection based on detection within a noisiersensor range.

An autonomous vehicle according to the present technology has amulti-level sensor range, wherein a first, less precise level of thesensor range is adjacent an outer bounds of the sensor range, and asecond, more precise level of the sensor range is inside the firstrange. As such, the first range may have a lower associated confidencevalue than the second range. For example, objects detected within thefirst range are likely to actually be present with a first degree ofcertainty, while objects detected within the second range are likely toactually be present with a second degree of certainty which is higherthan the first.

In some cases, an object (e.g., house, foliage, parked car, etc.) may beblocking a sensor's view. In such cases, the “first range” may beimmediately adjacent to the occluded area, where a moving object wouldfirst emerge from occlusion but would still have a lower confidencevalue. The “second range” may be adjacent to the first range, butfurther downstream from the occluded area, where confidence values arehigher.

Driving situations in which early detection may be used may includethose in which the autonomous vehicle is expected to yield to othertraffic, such as when merging onto a highway, or when crossing one ormore lanes of traffic to make a left turn. Such early detection isparticularly advantageous when oncoming traffic is traveling at a highrate of speed, such as 50 mph or above. In such instances, it may taketoo long for the autonomous vehicle to receive higher quality detectionin time to take the required driving action safely, such as merging orturning. By responding to noisier detections, or objects perceived witha lower degree of confidence, an appropriate driving action can safelybe taken earlier, and thus within time before the detected objectbecomes too close. The appropriate driving action may be, for example,waiting to merge or turn until no oncoming objects are detected within afield of view of the sensors.

Detecting objects within the first sensor range, having the lowerconfidence value, may produce false positives. However, responding as ifan object is present, when it actually is not, is typically a saferresponse.

The sensors used to detect objects may include any of a variety ofsensors, including those typically included in autonomous vehicles. Forexample, the sensors may include radar, LIDAR, sonar, or cameras.

In some examples, a confidence level of objects detected within thefirst sensor range may be improved using various techniques. Forexample, input received from sensors within the first sensor range maybe filtered, such that only detections at or above a thresholdsignal-to-noise ratio (SNR) will trigger a reaction. This reaction maybe different than a reaction to a detection confirmed in the secondsensor range. For example, a preliminary reaction triggered by detectionwithin the first sensor range may include limited braking, whereas aconfirmed detection in the second sensor range may trigger full braking.In other examples, different types of sensors may be used to detect theobject within the first sensor range, and the input from those differenttypes of sensors may be cross-validated. For example, if both a radarsensor and a LIDAR sensor detected the object within the first sensorrange, the object may be determined to be present. In contrast, if onlythe radar sensor detected the object within the first sensor range, andthe LIDAR did not, the object may be determined to not actually bepresent.

In other examples, a confidence level of objects detected across apipeline of both the first sensor range and the second sensor range mayalso be improved. For example, in addition to extracting features from acurrent set of perception data, such as SNR, cross-validation, etc., theobject may be tracked temporally over multiple iterations of perceptiondata. For example, object properties having temporal elements, such asspeed and acceleration, may be tracked.

Example Systems

As shown in FIG. 1, a vehicle 100 in accordance with one aspect of thedisclosure includes various components. While certain aspects of thedisclosure are particularly useful in connection with specific types ofvehicles, the vehicle may be any type of vehicle including, but notlimited to, cars, trucks, motorcycles, buses, recreational vehicles,etc. The vehicle may have one or more computing devices, such ascomputing devices 110 containing one or more processors 120, memory 130and other components typically present in general purpose computingdevices.

The memory 130 stores information accessible by the one or moreprocessors 120, including instructions 132 and data 134 that may beexecuted or otherwise used by the processor 120. The memory 130 may beof any type capable of storing information accessible by the processor,including a computing device-readable medium, or other medium thatstores data that may be read with the aid of an electronic device, suchas a hard-drive, memory card, ROM, RAM, DVD or other optical disks, aswell as other write-capable and read-only memories. Systems and methodsmay include different combinations of the foregoing, whereby differentportions of the instructions and data are stored on different types ofmedia.

The instructions 132 may be any set of instructions to be executeddirectly (such as machine code) or indirectly (such as scripts) by theprocessor. For example, the instructions may be stored as computingdevice code on the computing device-readable medium. In that regard, theterms “instructions” and “programs” may be used interchangeably herein.The instructions may be stored in object code format for directprocessing by the processor, or in any other computing device languageincluding scripts or collections of independent source code modules thatare interpreted on demand or compiled in advance. Functions, methods androutines of the instructions are explained in more detail below.

The data 134 may be retrieved, stored or modified by processor 120 inaccordance with the instructions 132. For instance, although the claimedsubject matter is not limited by any particular data structure, the datamay be stored in computing device registers, in a relational database asa table having a plurality of different fields and records, XMLdocuments or flat files. The data may also be formatted in any computingdevice-readable format.

The one or more processors 120 may be any conventional processors, suchas commercially available CPUs. Alternatively, the one or moreprocessors may be a dedicated device such as an ASIC or otherhardware-based processor. Although FIG. 1 functionally illustrates theprocessor, memory, and other elements of computing devices 110 as beingwithin the same block, it will be understood by those of ordinary skillin the art that the processor, computing device, or memory may actuallyinclude multiple processors, computing devices, or memories that may ormay not be stored within the same physical housing. For example, memorymay be a hard drive or other storage media located in a housingdifferent from that of computing devices 110. Accordingly, references toa processor or computing device will be understood to include referencesto a collection of processors or computing devices or memories that mayor may not operate in parallel.

Computing devices 110 may include all of the components normally used inconnection with a computing device such as the processor and memorydescribed above as well as a user input 150 (e.g., a mouse, keyboard,touch screen and/or microphone) and various electronic displays (e.g., amonitor having a screen or any other electrical device that is operableto display information). In this example, the vehicle includes aninternal electronic display 152 as well as one or more speakers 154 toprovide information or audio visual experiences. In this regard,internal electronic display 152 may be located within a cabin of vehicle100 and may be used by computing devices 110 to provide information topassengers within the vehicle 100.

Computing devices 110 may also include one or more wireless networkconnections 156 to facilitate communication with other computingdevices, such as the client computing devices and server computingdevices described in detail below. The wireless network connections mayinclude short range communication protocols such as Bluetooth, Bluetoothlow energy (LE), cellular connections, as well as various configurationsand protocols including the Internet, World Wide Web, intranets, virtualprivate networks, wide area networks, local networks, private networksusing communication protocols proprietary to one or more companies,Ethernet, WiFi and HTTP, and various combinations of the foregoing.

In one example, computing devices 110 may be control computing devicesof an autonomous driving computing system or incorporated into vehicle100. The autonomous driving computing system may capable ofcommunicating with various components of the vehicle in order to controlthe movement of vehicle 100 according to primary vehicle control code ofmemory 130. For example, returning to FIG. 1, computing devices 110 maybe in communication with various systems of vehicle 100, such asdeceleration system 160, acceleration system 162, steering system 164,signaling system 166, navigation system 168, positioning system 170,perception system 172, and power system 174 (i.e. the vehicle's engineor motor) in order to control the movement, speed, etc. of vehicle 100in accordance with the instructions 134 of memory 130. Again, althoughthese systems are shown as external to computing devices 110, inactuality, these systems may also be incorporated into computing devices110, again as an autonomous driving computing system for controllingvehicle 100.

As an example, computing devices 110 may interact with one or moreactuators of the deceleration system 160 and/or acceleration system 162,such as brakes, accelerator pedal, and/or the engine or motor of thevehicle, in order to control the speed of the vehicle. Similarly, one ormore actuators of the steering system 164, such as a steering wheel,steering shaft, and/or pinion and rack in a rack and pinion system, maybe used by computing devices 110 in order to control the direction ofvehicle 100. For example, if vehicle 100 is configured for use on aroad, such as a car or truck, the steering system may include one ormore actuators to control the angle of wheels to turn the vehicle.Signaling system 166 may be used by computing devices 110 in order tosignal the vehicle's intent to other drivers or vehicles, for example,by lighting turn signals or brake lights when needed.

Navigation system 168 may be used by computing devices 110 in order todetermine and follow a route to a location. In this regard, thenavigation system 168 and/or data 134 may store detailed mapinformation, e.g., highly detailed maps identifying the shape andelevation of roadways, lane lines, intersections, crosswalks, speedlimits, traffic signals, buildings, signs, real time trafficinformation, vegetation, or other such objects and information.

Positioning system 170 may be used by computing devices 110 in order todetermine the vehicle's relative or absolute position on a map or on theearth. For example, the position system 170 may include a GPS receiverto determine the device's latitude, longitude and/or altitude position.Other location systems such as laser-based localization systems,inertial-aided GPS, or camera-based localization may also be used toidentify the location of the vehicle. The location of the vehicle mayinclude an absolute geographical location, such as latitude, longitude,and altitude as well as relative location information, such as locationrelative to other cars immediately around it which can often bedetermined with less noise than absolute geographical location.

The positioning system 170 may also include other devices incommunication with computing devices 110, such as an accelerometer,gyroscope or another direction/speed detection device to determine thedirection and speed of the vehicle or changes thereto. By way of exampleonly, an acceleration device may determine its pitch, yaw or roll (orchanges thereto) relative to the direction of gravity or a planeperpendicular thereto. The device may also track increases or decreasesin speed and the direction of such changes. The device's provision oflocation and orientation data as set forth herein may be providedautomatically to the computing devices 110, other computing devices andcombinations of the foregoing.

The perception system 172 also includes one or more components fordetecting objects external to the vehicle such as other vehicles,obstacles in the roadway, traffic signals, signs, trees, etc. Forexample, the perception system 172 may include lasers, sonar, radar,cameras and/or any other detection devices that record data which may beprocessed by computing device 110. In the case where the vehicle is apassenger vehicle such as a minivan, the minivan may include a laser orother sensors mounted on the roof or other convenient location. Forinstance, FIG. 2 is an example external view of vehicle 100. In thisexample, roof-top housing 210 and dome housing 212 may include a lidarsensor as well as various cameras and radar units. In addition, housing220 located at the front end of vehicle 100 and housings 230, 232 on thedriver's and passenger's sides of the vehicle may each store a lidarsensor. For example, housing 230 is located in front of driver door 260.Vehicle 100 also includes housings 240, 242 for radar units and/orcameras also located on the roof of vehicle 100. Additional radar unitsand cameras (not shown) may be located at the front and rear ends ofvehicle 100 and/or on other positions along the roof or roof-top housing210.

The computing devices 110 may control the direction and speed of thevehicle by controlling various components. By way of example, computingdevices 110 may navigate the vehicle to a destination locationcompletely autonomously using data from the detailed map information andnavigation system 168. Computing devices 110 may use the positioningsystem 170 to determine the vehicle's location and perception system 172to detect and respond to objects when needed to reach the locationsafely. In order to do so, computing devices 110 may cause the vehicleto accelerate (e.g., by increasing fuel or other energy provided to theengine by acceleration system 162), decelerate (e.g., by decreasing thefuel supplied to the engine, changing gears, and/or by applying brakesby deceleration system 160), change direction (e.g., by turning thefront or rear wheels of vehicle 100 by steering system 164), and signalsuch changes (e.g., by lighting turn signals of signaling system 166).Thus, the acceleration system 162 and deceleration system 160 may be apart of a drivetrain that includes various components between an engineof the vehicle and the wheels of the vehicle. Again, by controllingthese systems, computing devices 110 may also control the drivetrain ofthe vehicle in order to maneuver the vehicle autonomously.

FIG. 3 illustrates an example of defined sensor ranges, whereindifferent vehicle responses may be triggered by detection of objects inthe different sensor ranges. As mentioned above, the vehicle 100 has oneor more sensors, such as radar, LIDAR, cameras, etc. The one or moresensors have an outer bound of reach, illustrated by boundary 310. Forexample, the boundary 310 may represent an extent of a field of view ofthe one or more sensors, such that the sensors do not detect objectsoutside the boundary 310. In some examples, the sensor field of view maybe occluded, such as by a tree, building, etc. In this case, the outerboundary 310 may be at least partially defined by the occluding object.In other examples, a distance between the sensor on the vehicle and theouter boundary 310 may depend on, for example, the type of sensor used.For example, a radar sensor may have a reach of approximately 160-200 m,while a LIDAR sensor may have a reach of approximately 85-160 m.

Within the outer boundary 310 is a first sensor range 315. The firstsensor range has a first confidence value associated therewith. Sensorsignals reaching the first range and near the outer boundary 310 may benoisy because of long range and/or short distance traversed inside areach of the sensor (e.g., less time within a sensor field of view).Accordingly, the first confidence value may be relatively low.

Within the first range sensor range 315, and closer to the vehicle 100,is second sensor range 325. Boundary 320 may define the first sensorrange 315 from the second sensor range 325. The second sensor range 325may be, for example, approximately 10-30 m shorter in range than thefirst sensor range 315, or more. The second sensor range 325 isassociated with a second confidence value. Signals within the secondsensor range 325 are less noisy and more precise than sensor signalswithin the first sensor range, because the signals in the second sensorrange 325 are not as far reaching as those in the first sensor range315. Accordingly, the second confidence value is higher than the firstconfidence value.

According to some examples, the boundary 320 between the first sensorrange 315 and the second sensor range 325 may be determined based onsignal quality, distance from or bearing to the one or more sensors,and/or other factors. By way of example only, the boundary 320 may beset at a threshold distance, a threshold signal to noise ratio, or somecombination thereof. In this regard, the boundary 320 may be variedalong with changes in signal quality. In other examples, the boundary320 may be redefined to accommodate for other factors, such as weather,visibility, sensor degradation, etc.

While only two sensor ranges are defined in the example described above,it should be understood that additional sensor ranges may also bedefined, such as a third sensor range, fourth sensor range, etc.

Different actions of the vehicle 100 may be triggered based on thesensor range in which an object is detected. For example, if an objectis detected in the first sensor range 315, the vehicle 100 may take apreliminary action, such as yielding, decelerating, ceasingacceleration, changing lanes, waiting, etc. If the object moves withinthe second sensor range 325, however, the vehicle 100 may take adifferent responsive action, such as stopping, or another action. Insome examples, detection of the object within the second range 325 mayserve as a verification of the previous detection of the object withinthe first range 315. In this regard, the first action taken in responseto the first detection may be considered a preliminary action inpreparation for the second action taken in response to the seconddetection.

Example Methods

In addition to the operations described above and illustrated in thefigures, various operations will now be described. It should beunderstood that the following operations do not have to be performed inthe precise order described below. Rather, various steps can be handledin a different order or simultaneously, and steps may also be added oromitted.

FIG. 4 is a flow diagram illustrating an example method of designatingmultiple ranges of sensor field of view, and operating an autonomousvehicle in response to detection of objects in one of the multipleranges.

In block 410, a first sensor range is defined at an outer bounds of afield of view of one or more sensors on a vehicle. The first sensorrange has a first associated confidence value. The first confidencevalue may be determined based on, for example, signal quality, errorrate, or other information. Because the first sensor range is near anouter bounds of the field of view, input signals received at the one ormore sensors are likely to be noisier than other portions of the fieldof view. Accordingly, the confidence value for the first sensor rangemay be relatively low as compared to other portions of the field ofview.

In block 420, a second sensor range is defined, wherein the secondsensor range is closer to the one or more sensors than first sensorrange, such as shown in FIG. 3. The second sensor range has a secondassociated confidence value, wherein the second confidence value ishigher than the first confidence value. For example, signals within thesecond sensor range, which travel less distance relative to signalstraveling to the first sensor range, may be more accurate and lessnoisy. Additionally, objects that have come within the second range havetraveled a greater distance within the overall detectable range. Aboundary between the first sensor range and the second sensor range maybe determined, for example, based on the associated confidence values orother accuracy quantifiers. For example, the boundary may be set basedon a threshold distance, a threshold confidence value, or the like.

In block 430, one or more processors of the vehicle receive input fromthe one or more sensors. According to some examples, where the one ormore sensors include a plurality of different types of sensors, thereceived input may include input from multiple sources.

In block 440, an object within the first sensor range is detected basedon the received input. The object may be, for example, a pedestrian, acyclist, another vehicle, or any other object the vehicle should avoid.In many examples, the object may be moving or about to move. Forexample, the object may be approaching the vehicle on the driver side asthe vehicle prepares to make a left turn. In other examples, the objectmay be approaching the vehicle from behind as the vehicle travels on aroadway. In other examples, the object may be traveling in a right laneof a highway onto which the vehicle is waiting to merge. While these aremerely a few examples, it should be understood that the object may bedetected in any of a number of circumstances. In the example wheremultiple sensors of different types are providing input to one or moreprocessors, the object may be detected by two or more of the differenttypes of sensors. The signals from the different types of sensors maythus be used to cross-validate one another.

In block 450, in response to detecting the object within the firstsensor range, the vehicle is triggered to take a first action prior tothe object being detected within the second sensor range. The firstaction may be, for example, waiting to turn or merge, decelerating,ceasing acceleration, or another precautionary action.

In some examples, taking the action in response to detecting the objectwithin the first sensor range may be limited based on further criteria.For example, the action may only be taken if the signal to noise ratioof signals detecting the object is at or above a predeterminedthreshold, such as by filtering out signals with a signal to noise ratiobelow the predetermined threshold. Where different types of sensors areused to cross-validate one another, the action may only be taken if theinput is cross-validated.

In some examples, the method may further include detecting, based onfurther input received from the one or more sensors, that the object hasmoved into the second sensor range of the vehicle. In such examples thedetection of the object within the second range may be used to validatethe detection of the object in the first range. Accordingly, the vehiclemay take a secondary action in response, such as stopping, continuing towait, etc.

FIGS. 5-8 illustrate some example scenarios in which the vehicleresponds to detection of objects within the first sensor range. As shownin FIG. 5, the vehicle 100 is traveling on an entry ramp 560 to roadway550. The roadway 550 may be a high speed roadway, such as where vehiclestravel approximately 40 miles per hour and faster. The second sensorrange 325, which has a perimeter closer to the vehicle 100 than thefirst sensor range 315, is clear. In other words, no objects aredetected within the second sensor range 325. If the vehicle 100 were torely solely on this indication from the second sensor range 325, it mayproceed to enter the roadway 550 and either “cut off” the vehicle 500 orcause a collision or near-collision with the vehicle 550. The firstsensor range 315, however, includes the vehicle 500. Accordingly,although the first sensor range 315 may have a lower confidence value,its indication of oncoming vehicle may be heeded as precaution. As such,the vehicle 100 may yield to the vehicle 500, and wait to merge onto theroadway 550. If detection of the vehicle 500 in the first sensor range315 is a false positive, and no vehicle is actually present within thefirst sensor range 315, yielding or waiting should not cause any dangerdue to the limited nature of reactions triggered by detections withinthe first sensor range.

As shown in FIG. 6, the vehicle 500 has moved into the second sensorrange 325. Such detection of the vehicle 500 within the second sensorrange 325 may be used to validate the detection in the first sensorrange 315. According to some examples, such validation may be used foradjusting confidence values for future detections in the first sensorrange, calibrating sensors, training the one or more processors totrigger reactions for detections within the first sensor range, or forany other purpose. For example, if at a future time in a similarcircumstance the vehicle 100 detects an object resembling a vehiclewithin the first sensor range 315, the one or more processors of thevehicle 100 may determine with greater confidence that a vehicle isactually approaching.

As shown in the example of FIG. 7, while vehicle 700 is traveling on theroadway 550 towards the entrance ramp 560, it is so far away from thevehicle 100 that it is outside the field of view. In this example, themaximum sensor range of the vehicle 100 is sufficiently long that aclear field of view would indicate a sufficient buffer between thevehicle 100 and the vehicle 700 for the vehicle 100 to safely enterroadway 550. The vehicle 700 is beyond the outer bounds of the firstsensor range 315, and thus beyond a point of detection by any of thesensors on the vehicle 100. Because the vehicle 700 is outside the fieldof view, it may be far enough away from the vehicle 100 that the vehicle100 can safely enter the roadway 550. Accordingly, as both the first andsecond sensor ranges are clear and sufficiently large to safely detecttraffic, and no oncoming traffic is detected at even a low signal tonoise ratio, the vehicle 100 proceeds to merge onto the roadway 550.

FIG. 8 illustrates another scenario, where the vehicle 100 is planningto make an unprotected left turn onto roadway 850 along path 870. Anunprotected turn in this example is one where the vehicle 100 crosses alane of traffic that has the right of way. While the vehicle 100 muststop at stop sign 852, there are no signs, traffic lights, or otherrequirements for traffic traveling along the roadway 850 to stop, slowdown, yield, or the like. Thus, as the vehicle 100 makes a left turnthrough intersection 854 and into roadway 850, there is some risk that avehicle traveling towards the intersection 854, such as the vehicle 800,will collide with the vehicle 100 if the vehicle 100 enters theintersection 854. Accordingly, the vehicle 100 detects whether anyvehicles are approaching to avoid such a collision. To give the vehicle100 as much notice as possible, the vehicle 100 detects whether anyobjects are within the first sensor range 315. Accordingly, the vehicle100 may detect at least a portion of the vehicle 800. In response, thevehicle 100 may continue to wait at the stop sign 852 until the field ofview is clear.

Within the first sensor range 315, the vehicle 100 also detectspedestrian 880 who has begun crossing the roadway 850. Accordingly, inthis context the vehicle 100 may also respond to the pedestrian 880 bywaiting to make the turn.

While several examples of maneuvers by the vehicle 100 benefiting fromearly perception in the first sensor range are described above, itshould be understood that these examples are in no way limiting and thatthe technology may be applied in any of a number of other instances. Forexample, where traffic in an adjacent lane on a high speed roadway ismoving faster than the vehicle, the vehicle may benefit by earlydetection of such traffic. In response, the vehicle may change lanes ortake another precautionary action. Other examples may include anysituation in which the vehicle should yield to another vehicle which itcannot yet see with high confidence.

By observing and adhering to noisy signals at an outer bounds of asensor range, the vehicle may take a precautionary action which resultsin safer operation of the vehicle. For example, as opposed to requiringan abrupt deceleration and stop when an object is detected at a closerrange, the vehicle may prepare by ceasing acceleration. In addition toan improved riding experience for passengers of the vehicle, theprecautionary actions of the vehicle increase the safety of everyonesharing the roadway.

Unless otherwise stated, the foregoing alternative examples are notmutually exclusive, but may be implemented in various combinations toachieve unique advantages. As these and other variations andcombinations of the features discussed above can be utilized withoutdeparting from the subject matter defined by the claims, the foregoingdescription of the embodiments should be taken by way of illustrationrather than by way of limitation of the subject matter defined by theclaims. In addition, the provision of the examples described herein, aswell as clauses phrased as “such as,” “including” and the like, shouldnot be interpreted as limiting the subject matter of the claims to thespecific examples; rather, the examples are intended to illustrate onlyone of many possible embodiments. Further, the same reference numbers indifferent drawings can identify the same or similar elements.

The invention claimed is:
 1. A method for maneuvering a vehicle, themethod comprising: defining, for an autonomous vehicle having one ormore sensors, a first sensor range having a first associated confidencevalue, the first sensor range adjacent an outer bound of reach of theone or more sensors; defining a second sensor range, the second sensorrange having a second associated confidence value that is higher thanthe first confidence value, the second sensor range being within thefirst sensor range and closer to the one or more sensors than the firstsensor range; receiving, at one or more processors, input from the oneor more sensors; detecting, by the one or more processors based on theinput received from the one or more sensors, an object within the firstsensor range of the vehicle; and causing the vehicle to take a firstaction in response to detecting the object within the first sensorrange, prior to the object being detected within the second sensorrange, wherein the first action comprises at least one of yielding,ceasing acceleration, decelerating, or switching lanes.
 2. The method ofclaim 1, further comprising: detecting, by the one or more processorsbased on further input received from the one or more sensors, that theobject has moved into the second sensor range of the vehicle; andvalidating the detection of the object within the first sensor rangebased on the detection of the object within the second sensor range. 3.The method of claim 2, further comprising causing the vehicle to take asecond action in response to detecting the object in the second sensorrange.
 4. The method of claim 3, wherein the second action is differentfrom the first action.
 5. The method of claim 1, further comprising:determining, with the one or more processors, a signal to noise ratioassociated with the input received from the one or more sensors;filtering the input received from the one or more sensors to ignoresignals with a signal to noise ratio below a threshold value.
 6. Themethod of claim 1, wherein receiving the input from the one or moresensors comprises receiving a first type of input and receiving a secondtype of input, and further comprising: cross-validating the first typeof input and the second type of input.
 7. The method of claim 6, whereinfirst type of input is from a first sensor and the second type of inputis from a second sensor being of a different sensor type than the firstsensor.
 8. The method of claim 1, wherein: the vehicle, when receivingthe input from the one or more sensors, is waiting to merge onto aroadway having a speed limit of 45 miles per hour or higher; the objectdetected within the first sensor range is a second vehicle traveling onthe roadway; and the first action comprises continuing to wait to mergeonto the roadway.
 9. The method of claim 1, wherein: the vehicle, whenreceiving the input from the one or more sensors, is traveling in afirst lane of a roadway having a speed limit of 45 miles per hour orhigher; the object detected within the first sensor range is a secondvehicle traveling in the first or a second lane on the roadway, andapproaching the vehicle from behind; and the first action comprisesavoiding the lane in which the second vehicle is traveling.
 10. Themethod of claim 1, wherein: the vehicle, when receiving the input fromthe one or more sensors, is making an unprotected turn onto a roadway;the object detected within the first sensor range is a second vehicletraveling along the roadway towards the vehicle; and the first actioncomprises waiting to make the unprotected turn until the first andsecond sensor ranges are clear.
 11. A system, comprising: one or moresensors, the one or more sensors having: a first defined range adjacentan outer bound of reach of the one or more sensors, the first definedrange having a first associated confidence value; and a second definedrange within the first sensor range and closer to the one or moresensors than the first sensor range, the second defined range having asecond associated confidence value that is higher than the firstconfidence value; one or more processors in communication with the oneor more sensors, wherein the one or more processors are configured to:receive input from the one or more sensors; detect, based on the inputreceived from the one or more sensors, an object within the first sensorrange of the vehicle; and cause the vehicle to take a first action inresponse to detecting the object within the first sensor range, prior tothe object being detected within the second sensor range, wherein thefirst action comprises at least one of yielding, ceasing acceleration,decelerating, or switching lanes.
 12. The system of claim 11, whereinthe one or more processors are further configured to cause the vehicleto take a second action in response to detecting the object in thesecond sensor range.
 13. The system of claim 11, wherein the one or moreprocessors are further configured to: detect, based on further inputreceived from the one or more sensors, that the object has moved intothe second sensor range of the vehicle; and validate the detection ofthe object within the first sensor range based on the detection of theobject within the second sensor range.
 14. The system of claim 11,wherein the one or more processors are further configured to: determinea signal to noise ratio associated with the input received from the oneor more sensors; and filter the input received from the one or moresensors to ignore signals with a signal to noise ratio below a thresholdvalue.
 15. The system of claim 11, wherein: the one or more sensorscomprise at least a first sensor of a first type and a second sensor ofa second type different than the first type.
 16. The system of claim 15,wherein receiving the input from the one or more sensors comprisesreceiving a first type of input from the first sensor and receiving asecond type of input from the second sensor, and wherein the one or moreprocessors are further configured to cross-validate the first type ofinput and the second type of input.
 17. A vehicle, comprising: a drivingsystem including at least an acceleration system, a braking system, anda steering system; a perception system including at least one or moresensors, the one or more sensors having: a first defined range adjacentan outer bound of reach of the one or more sensors, the first definedrange having a first associated confidence value; and a second definedrange within the first sensor range and closer to the one or moresensors than the first sensor range, the second defined range having asecond associated confidence value that is higher than the firstconfidence value; a control system including at least one or moreprocessors in communication with the one or more sensors, wherein theone or more processors are configured to: receive input from the one ormore sensors; detect, based on the input received from the one or moresensors, an object within the first sensor range of the vehicle; andcause the vehicle to take a first action in response to detecting theobject within the first sensor range, prior to the object being detectedwithin the second sensor range, wherein the first action comprises atleast one of yielding, ceasing acceleration, decelerating, or switchinglanes.
 18. The vehicle of claim 17, wherein the vehicle is autonomous.19. The vehicle of claim 17, wherein: the vehicle, when receiving theinput from the one or more sensors, is waiting to merge onto a roadwayhaving a speed limit of 45 miles per hour or higher; the object detectedwithin the first sensor range is a second vehicle traveling on theroadway; and the first action comprises continuing to wait to merge ontothe roadway.
 20. The vehicle of claim 17, wherein: the vehicle, whenreceiving the input from the one or more sensors, is traveling in afirst lane of a roadway having a speed limit of 45 miles per hour orhigher; the object detected within the first sensor range is a secondvehicle traveling in the first or a second lane on the roadway, andapproaching the vehicle from behind; and the first action comprisesavoiding the lane in which the second vehicle is traveling.
 21. Thevehicle of claim 17, wherein: the vehicle, when receiving the input fromthe one or more sensors, is making an unprotected turn onto a roadway;the object detected within the first sensor range is a second vehicletraveling along the roadway towards the vehicle; and the first actioncomprises waiting to make the unprotected turn until the first andsecond sensor ranges are clear.